Search Results for "web find machine"
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Showing 41 open source projects for "web find machine"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Synapse Machine Learning
Simple and distributed Machine Learning
SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit, and OpenCV. ... -
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CleanVision
Automatically find issues in image datasets
CleanVision automatically detects potential issues in image datasets like images that are: blurry, under/over-exposed, (near) duplicates, etc. This data-centric AI package is a quick first step for any computer vision project to find problems in the dataset, which you want to address before applying machine learning. CleanVision is super simple -- run the same couple lines of Python code to audit any image dataset! The quality of machine learning models hinges on the quality of the data used to train them, but it is hard to manually identify all of the low-quality data in a big dataset. ... -
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PySR
High-Performance Symbolic Regression in Python and Julia
PySR is an open-source tool for Symbolic Regression: a machine learning task where the goal is to find an interpretable symbolic expression that optimizes some objective. Over a period of several years, PySR has been engineered from the ground up to be (1) as high-performance as possible, (2) as configurable as possible, and (3) easy to use. PySR is developed alongside the Julia library SymbolicRegression.jl, which forms the powerful search engine of PySR. -
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Automated Tool for Optimized Modelling
Automated Tool for Optimized Modelling
...How many times have you copy-and-pasted code from an old repository to re-use it in a new use case? ATOM is here to help solve these common issues. The package acts as a wrapper of the whole machine learning pipeline, helping the data scientist to rapidly find a good model for his problem. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Arize Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
Phoenix provides ML insights at lightning speed with zero-config observability for model drift, performance, and data quality. Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative)... -
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Metaflow
A framework for real-life data science
Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. -
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XState
State machines and statecharts for the modern web
JavaScript and TypeScript finite state machines and statecharts for the modern web. Statecharts are a formalism for modeling stateful, reactive systems. This is useful for declaratively describing the behavior of your application, from the individual components to the overall application logic. XState is a library for creating, interpreting, and executing finite state machines and statecharts, as well as managing invocations of those machines as actors. The following fundamental computer... -
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ClearML
Streamline your ML workflow
...The ClearML Server storing experiment, model, and workflow data, and supports the Web UI experiment manager, and ML-Ops automation for reproducibility and tuning. It is available as a hosted service and open source for you to deploy your own ClearML Server. The ClearML Agent for ML-Ops orchestration, experiment and workflow reproducibility, and scalability. -
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Cleanlab
The standard data-centric AI package for data quality and ML
...This package helps you find label issues and other data issues, so you can train reliable ML models. All features of cleanlab work with any dataset and any model. Yes, any model: PyTorch, Tensorflow, Keras, JAX, HuggingFace, OpenAI, XGBoost, scikit-learn, etc. If you use a sklearn-compatible classifier, all cleanlab methods work out-of-the-box. -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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visual-explainer
Agent skill + prompt templates that generate rich HTML pages
...The project includes prompt templates and automation logic that enable coding agents to generate visual summaries such as diff reviews, architecture overviews, plan audits, and structured data tables. Its primary goal is to bridge the readability gap between raw machine output and stakeholder-friendly documentation. By producing styled web pages instead of plain text logs, visual-explainer improves communication in engineering and AI workflows where clarity is critical. The tool is particularly useful in environments that rely on autonomous agents or CI pipelines that generate dense technical output. -
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JS Analyzer
Burp Suite extension for JavaScript static analysis
JS Analyzer is a powerful static analysis tool implemented as a Burp Suite extension that helps security researchers and web developers automatically uncover important artifacts in JavaScript files during web application testing. It parses JavaScript responses intercepted by Burp Suite and intelligently extracts API endpoints, full URLs (including cloud storage links), secrets like API keys or tokens, and email addresses while filtering out noise from irrelevant code patterns. ... -
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Java Tablesaw
Java dataframe and visualization library
...Descriptive stats: mean, min, max, median, sum, product, standard deviation, variance, percentiles, geometric mean, skewness, kurtosis, etc. Add tablesaw-core to your project. You can find the version number for the latest release in the release notes. -
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Best-of Python
A ranked list of awesome Python open-source libraries
This curated list contains 390 awesome open-source projects with a total of 1.4M stars grouped into 28 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! Ranked list of awesome python libraries for web... -
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pprof
pprof is a tool for visualization and analysis of profiling data
...It supports multiple profile types (CPU, heap, allocations, contention, etc.) and can present data as text tables, call graphs (via Graphviz/dot), flame graphs, and interactive web UIs. The tool helps developers find hot paths, quantify resource usage, and compare profiles across runs to validate performance changes. It is widely used in Go but also has bindings and exporters for other ecosystems, and the repository includes a Go package for reading and writing profiles programmatically. The pprof command can operate on local files or fetch from targets exposing profiling endpoints, supporting iterative, production-oriented workflows. ... -
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airda
airda(Air Data Agent
airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes. -
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treeminder
a free mind mapping tool, to especially assist decision making
I've been trying to develop an idea of a project, but the wide range of possibilities with all their outcomes, cons and pros and whatnot got my mind overloaded. There was no way I could keep or process that much information with my bare mind. So, I've checked the mind mapping tools available in the market, both free and commercial ones, yet they were either clunky or overkilling for my needs. Thus, I've made my own thing, and decided to share it with everyone who might find it useful for... -
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MentDB Projects
Generalized Interoperability and Strong AI
MentDB is an open-source platform driving research into next-generation AI and universal data exchange. Our architecture is built around the revolutionary Mentalese Query Language (MQL). MentDB Weak (Generalized Interoperability): A unified data layer enabling seamless data exchange and application integration (SOA, ETL, Data Quality). We eliminate data silos through a single, generalized data language. MentDB Strong (Strong AI / AGI): The framework for exploring and building Machine... -
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Mara Pipelines
A lightweight opinionated ETL framework, halfway between plain scripts
This package contains a lightweight data transformation framework with a focus on transparency and complexity reduction. Data integration pipelines as code: pipelines, tasks and commands are created using declarative Python code. PostgreSQL as a data processing engine. Extensive web ui. The web browser as the main tool for inspecting, running and debugging pipelines. GNU make semantics. Nodes depend on the completion of upstream nodes. No data dependencies or data flows. No in-app data processing: command line tools as the main tool for interacting with databases and data. Single machine pipeline execution based on Python's multiprocessing. ... -
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Rawgraphs app
A web interface to create custom vector-based visualizations
Inspired by and built on top of open-source projects. RAWGraphs is open to the community for contributions. Almost 30 visual models to visualize quantities, hierarchies, and time series and find insights in your data. Even though RAWGraphs is a web app, the data you insert will be processed only by your web browser. Save your project, or export it as a vector or raster image. Edit it within your favorite software. RAWGraphs is an open source data visualization framework built with the goal of making the visual representation of complex data easy for everyone. ... -
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TurboVNC
High-speed, 3D-friendly, TightVNC-compatible remote desktop software
TurboVNC is a high-performance, enterprise-quality version of VNC based on TightVNC, TigerVNC, and X.org. It contains a variant of Tight encoding that is tuned for maximum performance and compression with 3D applications (VirtualGL), video, and other image-intensive workloads. TurboVNC, in combination with VirtualGL, provides a complete solution for remotely displaying 3D applications with interactive performance. TurboVNC's high-speed encoding methods have been adopted by TigerVNC and... -
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PANDORA
Revolutionizing Biomedical Research with Advanced Machine Learning
PANDORA is a machine learning (ML) tool that can be used to integrate various data types, including clinical, transcriptome and microbiome data and find connections in large datasets. PANDORA can be easily installed using Docker, a pre-built version of the software can be pulled from DockerHub. In order to run a test instance of PANDORA, users will first need to prepare their local environment by downloading, installing, and configuring Docker. genular is a community behind SIMON an open-source Machine Learning KnowledgeDiscovery software, built by a vibrant community of people just like you! ... -
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Self-learning-Computer-Science
Resources to learn computer science in your spare time
...The author (an undergraduate CS student) assembled links to courses from institutions like MIT, UC Berkeley, Stanford, etc., covering mathematics, programming, data structures/algorithms, computer architecture, machine learning, software engineering and more. It’s aimed at learners who find traditional course structures restrictive and want a flexible, self-paced path through CS, with a focus on building depth and breadth rather than shortcut exam skills. The repository provides a roadmap, references, teaching materials, and sometimes the author’s own project examples, offering both guidance and community support. ... -
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Log4jScanner
A log4j vulnerability filesystem scanner and Go package
log4jscanner is a filesystem scanner and Go package that helps organizations quickly identify vulnerable Log4j components inside JARs and shaded dependencies. Instead of probing networks, it walks directories and archives, including nested JARs, to find version fingerprints and risky classes associated with the Log4Shell family of issues. The focus on static analysis makes it suitable for container images, build artifacts, and offline systems where active scanning isn’t feasible. Clear, machine-readable output allows the tool to plug into CI/CD checks and fleet-wide inventory jobs. ... -
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ML workspace
All-in-one web-based IDE specialized for machine learning
All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated. ... -
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Vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python
Data science solutions, insights, dashboards, machine learning, deployment. We start at 100GB. Vaex is a high-performance Python library for lazy Out-of-Core data frames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second. Visualization is done using histograms, density plots and 3d volume rendering, allowing interactive...
